Electronic devices are increasingly integrated into daily life. However, electronic devices to function and interact with human users effectively, the ability to understand and respond to spoken language is very important. Unfortunately, automated speech recognition has proven to be a very difficult task for computers to perform.
In the past, computers and other devices that use microelectronics have sought to interpret natural spoken language using acoustic models (which match sounds detected to known words) and language models, which allow a device to probabilistically rate the likelihood of a number of possible candidate words or phrases. Additional improvements to natural language processing would be useful in furthering the ability of these devices to interact with their human users.